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pashok25 [27]
2 years ago
10

Keith tabulated the following values for time spent napping in minutes of six of his friends: 23, 35, 17, 30, 20, and 19. The st

andard deviation is 7.043 Keith reads that the mean nap is 22 minutes. The t-statistic for a two-sided test would be __________. Answer choices are rounded to the hundredths place. 1.39 or 1.43 or 2.88 or 0.70
Mathematics
1 answer:
il63 [147K]2 years ago
3 0

Answer:

The  t-statistic is t  =  0.6956

Step-by-step explanation:

From the question we are told that

     The population mean is  \mu =  22 \ minutes

       The standard deviation is  s =  7.043

       The  given data is  23, 35, 17, 30, 20, and 19.

Generally the sample mean is mathematically evaluated as

      \=  x  =  \frac{23+  35+17+ 30+ 20+ 19 }{6}

     \=  x  =24

The t-statistic is mathematically evaluated as

       t  =  \frac{ \= x  - \mu }{\frac{s}{ \sqrt{n} } }

=>   t  =  \frac{ 24   - 22 }{\frac{ 7.043}{ \sqrt{6} } }

=>   t  =  0.6956

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Answer:

Y will arrive earlier than X one fourth of times.

Step-by-step explanation:

To solve this, we might notice that given that both events are independent of each other, the joint probability density function is the product of X and Y's probability density functions. For an uniformly distributed density function, we have that:

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Where L stands for the length of the interval over which the variable is distributed.

Now, as  X is distributed over a 1 hour interval, and Y is distributed over a 0.5 hour interval, we have:

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\iint_A f_{X,Y} (x,y) dx\, dy

Where A is the in which the event happens, in this case, the region in which Y<X (Y arrives before X)

It's useful to draw a diagram here, I have attached one in which you can see the integration region.

You can see there a box, that represents all possible outcomes for Y and X. There's a diagonal coming from the box's upper right corner, that diagonal represents the cases in which both X and Y arrive at the same time, under that line we have that Y arrives before X, that is our integration region.

Let's set up the integration:

\iint_A f_{X,Y} (x,y) dx\, dy\\\\\iint_A f_{X} (x) \, f_{Y} (y) dx\, dy\\\\2 \iint_A  dx\, dy

We have used here both the independence of the events and the uniformity of distributions, we take the 2 out because it's just a constant and now we just need to integrate. But the function we are integrating is just a 1! So we can take the integral as just the area of the integration region. From the diagram we can see that the region is a triangle of height 0.5 and base 0.5. thus the integral becomes:

2 \iint_A  dx\, dy= 2 \times \frac{0.5 \times 0.5 }{2} \\\\2 \iint_A  dx\, dy= \frac{1}{4}

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y - x = 10.40 -8.10 = 2.30

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